Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G
Liang Wu, Kelly Wan, Mayank Darbari, Liangjie Hong

TL;DR
This paper envisions 6G networks as AI-native systems with foundation models and multi-agent orchestration, aiming for resilient, autonomous, and intelligent communication infrastructure.
Contribution
It introduces a BlueSky vision for integrating foundation models and multi-agent systems into 6G for enhanced resilience and autonomy.
Findings
Proposes a 6G foundation model as a unified backbone.
Designs multi-agent systems for autonomous network management.
Outlines a roadmap for AI-native 6G evolution.
Abstract
The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster, but fundamentally more resilient and autonomous. This paper presents a BlueSky vision on how Artificial Intelligence will be natively integrated into 6G, shifting the paradigm from \underline{Network for AI} to \underline{AI for Network}. We envision that, unlike 5G's reliance on scattered, ad-hoc models each trained for a single task, native AI in the 6G era will be anchored by a foundation model and and orchestrated via collaborative multi-agent systems, framing network management as a unified, multi-modal, multi-task optimization problem. Built on this vision, we outline two transformative directions. The first focuses on developing a 6G foundation model as a unified backbone, with task-specific knowledge distilled into compact models…
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